A genome-wide positioning systems network algorithm for in silico drug repurposing

Cheng, Feixiong; Lü, Weiqiang; Liu, Chuang; Fang, Jiansong; Hou, Yuan; Handy, Diane E.; Wang, Rui-Sheng; Zhao, Yuzheng; Yang, Yi; Huang, Jin; Hill, David E.; Vidal, Marc; Eng, Charis; Loscalzo, Joseph

doi:10.1038/s41467-019-10744-6

Cited by 159 publications

(167 citation statements)

References 66 publications

Supporting

Mentioning

161

Contrasting

Order By: Relevance

“…For a drug with multiple targets to be effective against an HCoV, its target proteins should be within or in the immediate vicinity of the corresponding subnetwork in the human protein-protein interactome ( Fig. 1), as we demonstrated in multiple diseases 13,22,23,28 using this network-based strategy. We used a state-of-theart network proximity measure to quantify the relationship between HCoV-specific subnetwork ( Fig.…”

Section: Network-based Drug Repurposing For Hcovsmentioning

confidence: 90%

“…Here, drug-target interactions meeting the following three criteria were used: (i) binding affinities, including K i , K d , IC 50 , or EC 50 each ≤10 μM; (ii) the target was marked as "reviewed" in the UniProt database 91 ; and (iii) the human target was represented by a unique Uni-Prot accession number. The details for building the experimentally validated drug-target network are provided in our recent studies 13,23,28 .…”

Section: Building the Drug-target Networkmentioning

confidence: 99%

“…In total, the resulting human protein-protein interactome used in this study includes 351,444 unique PPIs (edges or links) connecting 17,706 proteins (nodes), representing a 50% increase in the number of the PPIs we have used previously. Detailed descriptions for building the human protein-protein interactome are provided in our previous studies 13,23,28,93 .…”

Section: Building the Human Protein-protein Interactomementioning

confidence: 99%

“…This methodology allows to identify several candidate repurposable drugs for Ebola virus 11,14 . Our work over the last decade has demonstrated how network strategies can, for example, be used to identify effective repurposable drugs 13,[22][23][24][25][26][27] and drug combinations 28 for multiple human diseases. For example, network-based drug-disease proximity sheds light on the relationship between drugs (e.g., drug targets) and disease modules (molecular determinants in disease pathobiology modules within the PPIs), and can serve as a useful tool for efficient screening of potentially new indications for approved drugs, as well as drug combinations, as demonstrated in our recent studies 13,23,27,28 .…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

et al. 2020

Self Cite

View full text Add to dashboard Cite

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV-host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

show abstract

Section: Network-based Drug Repurposing For Hcovsmentioning

confidence: 90%

Section: Building the Drug-target Networkmentioning

confidence: 99%

Section: Building the Human Protein-protein Interactomementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Indeed, these are offering multilevel network analyses to identify key pathogenic nodes, including genes, protein, metabolites and their interactions in the human interactome, useful as innovative biomarkers and drug targets. [10][11][12][13] Network medicine is an integrative molecularbioinformatic approach useful to advance the current medical practices by overcoming the limitations of the reductionist concept viewing a disease as a direct consequence of a single molecular defect, still central in CV care. 7 11-14 Moreover, machine learning techniques applied to complex electronic health records are being used in clinical trials (NCT00303212) to develop prediction models useful to diagnosis, classification, readmissions and medication adherence in patients with heart failure (HF).…”

mentioning

confidence: 99%

Fluid-based assays and precision medicine of cardiovascular diseases: the ‘hope’ for Pandora’s box?

2019

View full text Add to dashboard Cite

Progresses in liquid-based assays may provide novel useful non-invasive indicators of cardiovascular (CV) diseases. By analysing circulating cells or their products in blood, saliva and urine samples, we can investigate molecular changes present at specific time points in each patient allowing sequential monitoring of disease evolution. For example, an increased number of circulating endothelial cells may be a diagnostic biomarker for diabetic nephropathy and heart failure with preserved ejection fraction. The assessment of circulating cell-free DNA (cfDNA) levels may be useful to predict severity of acute myocardial infarction, as well as diagnose heart graft rejection. Remarkably, circulating epigenetic biomarkers, including DNA methylation, histone modifications and non-coding RNAs are key pathogenic determinants of CV diseases representing putative useful biomarkers and drug targets. For example, the unmethylated FAM101A gene may specifically trace cfDNA derived from cardiomyocyte death providing a powerful diagnostic biomarker of apoptosis during ischaemia. Moreover, changes in plasma levels of circulating miR-92 may predict acute coronary syndrome onset in patients with diabetes. Now, network medicine provides a framework to analyse a huge amount of big data by describing a CV disease as a result of a chain of molecular perturbations rather than a single defect (reductionism). We outline advantages and challenges of liquid biopsy with respect to traditional tissue biopsy and summarise the main completed and ongoing clinical trials in CV diseases. Furthermore, we discuss the importance of combining fluid-based assays, big data and network medicine to improve precision medicine and personalised therapy in this field.

show abstract

Identifying miRNAs in multiple sclerosis gray matter lesions that correlate with atrophy measures

Tripathi

Pandit

Perles

et al. 2021

Ann Clin Transl Neurol

Self Cite

View full text Add to dashboard Cite

Objective: Multiple sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS). Though MS was initially considered to be a white matter demyelinating disease, myelin loss in cortical gray matter has been reported in all disease stages. We previously identified microRNAs (miRNAs) in white matter lesions (WMLs) that are detected in serum from MS patients. However, miRNA expression profiles in gray matter lesions (GMLs) from progressive MS brains are understudied. Methods: We used a combination of global miRNAs and gene expression profiling of GMLs and independent validation using real-time quantitative polymerase chain reaction (RT-qPCR), immuno-in situ hybridization, and immunohistochemistry. Results: Compared to matched myelinated gray matter (GM) regions, we identified 82 miRNAs in GMLs, of which 10 were significantly upregulated and 17 were significantly downregulated. Among these 82 miRNAs, 13 were also detected in serum and importantly were associated with brain atrophy in MS patients. The predicted target mRNAs of these miRNAs belonged to pathways associated with axonal guidance, TGF-b signaling, and FOXO signaling. Further, using state-of-the-art human protein-protein interactome network analysis, we mapped the four key GM atrophy-associated miRNAs (hsa-miR-149*, hsa-miR-20a, hsa-miR-29c, and hsa-miR-25) to their target mRNAs that were also changed in GMLs. Interpretation: Our study identifies miRNAs altered in GMLs in progressive MS brains that correlate with atrophy measures. As these miRNAs were also detected in sera of MS patients, these could act as markers of GML demyelination in MS.

show abstract

A genome-wide positioning systems network algorithm for in silico drug repurposing

Cited by 159 publications

References 66 publications

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Fluid-based assays and precision medicine of cardiovascular diseases: the ‘hope’ for Pandora’s box?

Identifying miRNAs in multiple sclerosis gray matter lesions that correlate with atrophy measures

Contact Info

Product

Resources

About